Using Comparable Corpora to Adapt a Translation Model to Domains

Statistical machine translation (SMT) requires a large parallel corpus, which is available only for restricted language pairs and domains. To expand the language pairs and domains to which SMT is applicable, we created a method for estimating translation pseudo-probabilities from bilingual comparable corpora. The essence of our method is to calculate pairwise correlations between the words associated with a source-language word, presently restricted to a noun, and its translations; word translation pseudo-probabilities are calculated based on the assumption that the more associated words a translation is correlated with, the higher its translation probability. We also describe a method we created for calculating noun-sequence translation pseudo-probabilities based on occurrence frequencies of noun sequences and constituent-word translation pseudo-probabilities. Then, we present a framework for merging the translation pseudo-probabilities estimated from in-domain comparable corpora wit...

• Type: Conference
• Year: 2010
• Where: LREC
• Authors: Hiroyuki Kaji, Takashi Tsunakawa, Daisuke Okada
• Keywords: Comparable Corpora, Education, LREC 2010, Parallel Corpus, Translation Pseudo-probabilities